CONUS-wide Projected Flood Frequency Estimates, Version 1.0

Ghimire, Ganesh; Kao, Shih-Chieh; Gangrade, Sudershan

doi:10.13139/OLCF/2575147

Title: CONUS-wide Projected Flood Frequency Estimates, Version 1.0

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Abstract

This dataset presents a large-ensemble of CONUS-wide projected flood frequency estimates across ~2.7 million NHDPlusV2 river reaches over the CONUS. The framework producing this dataset leverages a multi-model, uncertainty-aware modeling framework that allows evaluating shifts in flood frequencies at the stream reach level across the CONUS. CONUS-wide ensemble streamflow projections generated from hydrologic simulations driven by downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) outputs are used to derive these flood frequency estimates over the period 1980 - 2099. A spatially consistent regional L-moment algorithm is applied across clusters defined by the US Hydrologic Unit Code Subregions (HUC4s and HUC8s) and NHDPlusV2 stream orders to estimate flood frequencies. The dataset also includes at-site based flood estimates allowing for the distinction between local and regional approaches, assess projected changes, and characterize their uncertainties. For rare flood frequencies such as 500 and 1000-year return periods, super-ensemble based estimates are also included in the dataset. This dataset is derived to support the "Impact-Informed Dam Safety Risk Assessment for Securing Hydropower Assets" project for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). For further details, refer to Kao et al. (2022), Ghimire et al. (2023), and Ghimire et al.more » (2025).« less

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ORNL

Publication Date:: Wed Oct 01 00:00:00 EDT 2025

DOE Contract Number:: AC05-00OR22725

Research Org.:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE); USDOE

OSTI Identifier:: 3001986

DOI:: https://doi.org/10.13139/OLCF/2575147

Citation Formats


                    Ghimire, Ganesh, Kao, Shih-Chieh, and Gangrade, Sudershan. CONUS-wide Projected Flood Frequency Estimates, Version 1.0.  United States: N. p., 2025. 
        Web.  doi:10.13139/OLCF/2575147.

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                    Ghimire, Ganesh, Kao, Shih-Chieh, & Gangrade, Sudershan. CONUS-wide Projected Flood Frequency Estimates, Version 1.0.  United States.  doi:https://doi.org/10.13139/OLCF/2575147

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                    Ghimire, Ganesh, Kao, Shih-Chieh, and Gangrade, Sudershan. 2025.  
"CONUS-wide Projected Flood Frequency Estimates, Version 1.0".  United States.  doi:https://doi.org/10.13139/OLCF/2575147.  https://www.osti.gov/servlets/purl/3001986. Pub date:Wed Oct 01 00:00:00 EDT 2025

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@article{osti_3001986,

  title        = {CONUS-wide Projected Flood Frequency Estimates, Version 1.0},

  author       = {Ghimire, Ganesh and Kao, Shih-Chieh and Gangrade, Sudershan},

  abstractNote = {This dataset presents a large-ensemble of CONUS-wide projected flood frequency estimates across ~2.7 million NHDPlusV2 river reaches over the CONUS. The framework producing this dataset leverages a multi-model, uncertainty-aware modeling framework that allows evaluating shifts in flood frequencies at the stream reach level across the CONUS. CONUS-wide ensemble streamflow projections generated from hydrologic simulations driven by downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) outputs are used to derive these flood frequency estimates over the period 1980 - 2099. A spatially consistent regional L-moment algorithm is applied across clusters defined by the US Hydrologic Unit Code Subregions (HUC4s and HUC8s) and NHDPlusV2 stream orders to estimate flood frequencies. The dataset also includes at-site based flood estimates allowing for the distinction between local and regional approaches, assess projected changes, and characterize their uncertainties. For rare flood frequencies such as 500 and 1000-year return periods, super-ensemble based estimates are also included in the dataset. This dataset is derived to support the "Impact-Informed Dam Safety Risk Assessment for Securing Hydropower Assets" project for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). For further details, refer to Kao et al. (2022), Ghimire et al. (2023), and Ghimire et al. (2025).},

  doi          = {10.13139/OLCF/2575147},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Wed Oct 01 00:00:00 EDT 2025},

  month        = {Wed Oct 01 00:00:00 EDT 2025}

}

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DOI: https://doi.org/10.13139/OLCF/2575147

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